Symptom control and health‐related quality of life in allergic rhinitis with and without comorbid asthma: A multicentre European study

Abstract Background Allergic rhinitis (AR) is a major non‐communicable disease that affects the health‐related quality of life (HRQoL) of patients. However, data on HRQoL and symptom control in AR patients with comorbid asthma (AR + asthma) are lacking. Methods In this multicentre, cross‐sectional study, patients with AR were screened and administered questionnaires of demographic characteristics and health conditions (symptoms/diagnosis of AR and asthma, disease severity level, and allergic conditions). HRQoL was assessed using a modified version of the RHINASTHMA questionnaire (30, ‘not at all bothered’ ‐ 150 ‘very much bothered’) and symptom control was evaluated by a modified version of the Control of Allergic Rhinitis/Asthma Test (CARAT) (0, ‘no control’ ‐ 30, ‘very high control’). Results Out of 643 patients with AR, 500 (78%) had asthma as a comorbidity, and 54% had moderate‐severe intermittent AR, followed by moderate‐severe persistent AR (34%). Compared to the patients with AR alone, patients with AR + asthma had significantly higher RHINASTHMA (e.g., median RHINASTHMA‐total score 48.5 vs. 84, respectively) and a significantly lower CARAT score (median CARAT‐total score 23 vs. 16.5, respectively). Upon stratifying asthma based on severity, AR patients with severe persistent asthma had worse HRQoL and control than those with mild persistent asthma. The association was significantly higher among non‐obese participants compared to obese ones, with RHINASTHMA‐upper symptoms score but not with CARAT. Conclusions Our observation of poorer HRQoL and symptoms control in AR patients with comorbid asthma supports the importance of a comprehensive approach for the management of AR in case of a comorbid allergic condition.


| INTRODUCTION
Allergic rhinitis (AR) is a type-2 chronic inflammatory disease affecting the nasal mucosa and characterized by nasal symptoms such as sneezing, rhinorrhoea (nasal discharge), pruritus, and nasal congestion. [1][2][3] It is one of the most common non-communicable chronic diseases in the world, affecting over 400 million people of all ages, particularly the paediatric population. [1][2][3][4][5][6] While the prevalence of physician-diagnosed AR in the United States has been observed as high as 15% and 30%, based on self-reported nasal symptoms, 7,8 the prevalence was as high as up to 50% in many European countries. 9 According to the Allergic Rhinitis and its Impact on Asthma (ARIA) and the Global Alliance against Chronic Respiratory Diseases (GARD) statements, severe, refractory, or mixed forms of AR are significantly increasing across the globe and have contributed substantially to the socio-economic burden of the disease. [10][11][12] Allergic rhinitis often coexists with other conditions, such as atopic dermatitis, rhinosinusitis, rhino-conjunctivitis, and particularly asthma -a coherent feature often referred to as 'the atopic March' due to common systemic inflammatory processes. 2,4 40%-50% of patients with AR also have asthma whereas the prevalence of AR as a comorbidity in asthmatic patients is even higher, that is, 70%-90%. 13 Several reports described that the patients suffering from AR show a poorer quality of life (QoL), being affected by impaired sleep patterns, increased amount of fatigue, depression, risk of driving accident, and altered physical and social functions. 8,[14][15][16] Often, a poor perception of AR symptoms is associated with poor control of AR. 17 However, studies assessing health-related quality of life (HRQoL) and symptoms control in AR patients with concomitant asthma are lacking.
The Aerobiological Information Systems and allergic respiratory disease management (AIS Life +) study focused on this aspect, by using specifically designed and validated questionnaires on QoL and control for AR with comorbid asthma. In this multicentre study, using validated questionnaires, we aimed to assess the differences in symptom control and HRQoL between AR patients with or without comorbid asthma.

| Study design and participants
In the international multi-centre (Austria, France, and Italy) crosssectional AIS Life + study, conducted between 2013 and 2014, we enrolled participants suffering from nasal allergy. A convenient sample of individuals with an active condition of pollen-induced AR was selected from pre-existing epidemiological study databases or through web advertisement (Pisa, Italy), clinics of general practitioners (Paris, France) or public health databases and pulmonary clinics (Vienna, Austria) and invited to participate in this epidemiological survey. All potential participants were administered a screening questionnaire through a telephone interview to check whether they were eligible for the study. We included participants who: (1) were adults (≥18 years of either sex); (2)   and ARIA (2008) 6 were used to classify asthma according to its severity. Control of Allergic Rhinitis/Asthma Test is available in several languages including those of the participating countries.

| Statistical analyses
Data were described as frequency (%), mean (standard deviation [SD]), or median (interquartile range [IQR]) for categorical, continuous, and ordinal variables, respectively. To test the association between QoL and control (RHINASTHMA and CARAT -Total and subdomains) scores, and AR + asthma (independent variable), we first used a bivariate analysis using Wilcoxon rank-sum test. Then, we constructed univariable (unadjusted) and multivariable (adjusted) regression models among the independent variable and HRQoL and control scores using a mixed effect Poisson regression model. As potential confounders, we tested fixed factors (age, sex, BMI, smoking status, exposure to smoke, education, ARIA grade, sensitivity to allergens, and drugs taken in the last 12 months) and a random factor (the country). To include confounders in the regression models, we used a priori evidence criteria, that is, covariates were considered as confounders if were found consistent in previous literature. However, confounders were retained in the model if they modified the estimates of the remaining variables by more than 10%. We checked the collinearity of the confounders using the variance inflation factor (VIF). The parsimony of the models was confirmed by Akaike information criterion.
We also performed two secondary analyses. Firstly, we tested if there was any effect modification by obesity on the association between AR + asthma, and the HRQoL and control scores. Secondly, we performed meta-analyses to determine if there were any heterogeneity in the HRQoL and control (total) scores between the participating countries. All analyses were conducted using a complete case approach in Stata V.16 (StataCorp, College Station, TX, USA), and a pvalue <0.05 was considered statistically significant.

| RESULTS
The demographic and clinical characteristics of all the participants, stratified by country, are presented in Table 1. Of all participants, nearly 40% were males with a mean age of 44 (standard deviation, SD: 14) years, 15% of the participants were obese, 47% were smokers and nearly 33% reported exposure to smoke, 78% of the participants had asthma as comorbidity, 54% had moderate-severe intermittent AR and 34% had moderate-severe persistent AR. As for allergic sensitization, pollens were the most prevalent allergen (89%) among the participants, followed by house dust mites (57%).
Concerning the HRQoL parameters, the participants had a median (IQR) RHIN-Total score of 76 (53, 91) and CARAT-Total score of 18 (14,22). In the bivariate analysis, we found that participants with both AR and asthma had significantly higher RHINASTHMA (Total and subdomain) scores than the participants with AR alone (Figure 1). MOITRA ET AL.  Moreover, CARAT (Total and subdomain) scores were significantly lower in AR with comorbid asthma than in AR alone ( Figure 2).
In the multivariable analysis, we observed that, compared to AR alone, AR with comorbid asthma was significantly associated with  (Figure 3 and Supplementary Table 1). We did not find any multicollinearity between the covariates (VIF<3).
We observed a poorer control of symptoms in AR patients with asthma comorbidity than in patients with AR alone (β for CARAT-   Table 4).
However, the overall estimates from the meta-analyses for the association between AR + asthma, and RHIN-Total and CARAT-Total scores were similar to the ones reported in the main analysis.

| DISCUSSION
In our study, we found a significantly worse QoL (RHINASTHMA Total and subdomain scores) and symptoms control (CARAT Total and subdomain scores) in patients with AR + asthma than in patients with AR alone. We also found that the association was significantly higher among non-obese participants compared to obese ones, when assessed through RHIN-Upper symptoms score but not with CARAT.
F I G U R E 2 Differences in CARAT-Total and subdomain scores between patients with Allergic rhinitis (AR) alone and AR + asthma. Data presented as median (solid line) and interquartile range (IQR) (dashed line) unless otherwise stated. P-values were calculated from the Wilcoxon-ranked sum test F I G U R E 3 Adjusted association between AR + asthma and RHINASTHMA-Total and subdomain scores. Data presented as regression coefficient (β) (symbol) and 95% confidence interval (CI) (horizontal bar) unless otherwise stated. Models were adjusted for age, sex, body mass index (BMI), smoking status, exposure to smoke, education, Allergic Rhinitis and its Impact on Asthma (ARIA) grade, sensitivity to allergens, and drugs taken in the last 12 months as fixed factors, and the country as a random factor We also observed country-specific variations in the RHINASTHMA and CARAT Total scores. Although one previous study compared the individual/social burden of disease between asthmatics and asthmatics with concomitant AR, unlike ours, that study did not compare the difference in disease control and HRQoL between the two groups of patients. 25 It is well-known that several triggers such as seasonal meteorological changes, pollen season, air pollution, or even occupational F I G U R E 5 Meta-analysis results of the association between AR + asthma and (A) RHIN-Total score and (B) CARAT-Total score, stratified by countries. Models were adjusted for sex, age, smoking status, exposure to smoke, education, Allergic Rhinitis and its Impact on Asthma (ARIA) grade, sensitivity to allergens, and drugs taken in the last 12 months as fixed factors. I-squared, variation in estimated effect attributable to heterogeneity F I G U R E 4 Adjusted association between AR + asthma and CARAT-Total and subdomain scores. Data presented as regression coefficient (β) (symbol) and 95% confidence interval (CI) (horizontal bar) unless otherwise stated. Models were adjusted for age, sex, body mass index (BMI), smoking status, exposure to smoke, education, Allergic Rhinitis and its Impact on Asthma (ARIA) grade, sensitivity to allergens, and drugs taken in the last 12 months as fixed factors, and the country as a random factor exposures may lead to poor QoL of asthmatic patients with or without AR. 8,[26][27][28] It has also been observed that AR patients are often reported to have poor control over their symptoms if persistent comorbid asthma is present. [29][30][31][32] Although no direct comparative study on the control and HRQoL of AR and AR with asthma has been reported yet, our findings well reciprocate the previous results.
Asthma and AR share eight common genes (CLC, EMR4P, IL5RA, FRRS1, HRH4, SLC29A1, SIGLEC8, IL1RL1) that are presumed to describe the link for multimorbidity. 33 They also share common risk factors such as atopic genetic background (for the allergic endotypes), environmental exposures (allergens, moulds, indoor and outdoor air pollution, some respiratory viruses, etc.), type of occupation, and active tobacco smoking.
We found that the non-obese patients with AR + asthma had  36 Our result could also be influenced by other factors such as physical activity or environmental conditions; however, we could not confirm them in our study.
We found significant country-wise heterogeneity in RHI-NASTHMA and CARAT-Total scores between AR alone and AR + asthma. This could be explained by a higher number of AR + asthma patients in France than in the two other countries.
Another reason for such heterogeneity could be due to significant variation in allergen sensitivity between the countries, which has also been previously reported describing a significant difference in aeroallergens and allergies between European countries. [37][38][39] Air pollution is another important perturbation that can significantly affect HRQoL and symptom control in allergic patients and a recent metaanalysis suggested that there is significant variability in air pollution between different European counties that have differently attributed to the risk of AR. 40 However, studying air pollution was beyond the scope of our current study. Nevertheless, this variation of HRQoL and control could also be influenced by other, such as co-occurrence of any food allergies, and other environmental conditions, which we could not assess in this current study.
Our findings add important clinical knowledge to the existing strategies for the management of AR with concomitant asthma.
Although AR and asthma are two different diseases with distinct clinical features, when AR persists with asthma, either condition is often overlooked 32,41 due to the lack of a combined tool for monitoring control and HRQoL of both diseases at the same time. Despite the well-established guidelines of ARIA and GARD for a new management protocol for AR and asthma together, 10,12,[42][43][44][45] reports adopting these guidelines in the management of AR with persistent asthma are still lacking. Our findings would help guide practitioners to use the appropriate assessment tools while treating such patients.
Our study recruited patients from three European countries which have distinct geographical, climatic, and aerobiological conditions. Moreover, we recorded sensitivity data to a wide variety of indoor and outdoor allergens which enabled us to observe the distribution of those allergens across the participant countries. Our meta-analytic approach to assessing country-wise variation in HRQoL and control provides a novel understanding of the divergent population and their disease conditions. Our findings underline the impact of respiratory hypersensitivity conditions on the QoL of patients and call for prevention and public health strategies to diminish the burden of these conditions. Currently, there are effective treatments for AR and asthma, several risk factors are known (e.g., allergies, rhinitis, tobacco smoke) and tools to control the disease have been developed.

| CONCLUSION
In summary, using combined assessment tools for AR and asthma, we found that AR patients with comorbid asthma have a poorer quality of life and symptom control than those with AR alone. This finding highlights the importance of a comprehensive approach for the management of AR in case of a comorbid allergic condition for optimum care, and such strategies would be the gateway to reducing the global burden of these diseases.